AI-to-AI Feedback: Amplified Intelligence — Prior Art and Governance Implications for Multi-Model Advisory Architectures

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1. Verfasser: Ruocco, Pantaleone
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Veröffentlicht: Zenodo 2026
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author Ruocco, Pantaleone
author_facet Ruocco, Pantaleone
contents This paper establishes the independent prior art of the AI-to-AI Feedback framework, a multi-model advisory architecture first developed and publicly documented by the author on 10 May 2025. On 9 April 2026, Anthropic released the Advisor Strategy on the Claude Platform, implementing a functionally equivalent architecture. On 2 October 2025, Asawa et al. at UC Berkeley published a related approach. This paper presents a detailed chronological record, a structural comparison across all three works, and identifies the governance gap that remains unaddressed. The authors related patent filings for CRE (Claude Rule Enforcer, GB2604445.3) and HookBus (GB2608069.7) are presented as complementary governance solutions.
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spellingShingle AI-to-AI Feedback: Amplified Intelligence — Prior Art and Governance Implications for Multi-Model Advisory Architectures
Ruocco, Pantaleone
AI-to-AI feedback
intelligence amplification
multi-model architecture
advisor strategy
prior art
AI governance
agentic systems
CRE
HookBus
This paper establishes the independent prior art of the AI-to-AI Feedback framework, a multi-model advisory architecture first developed and publicly documented by the author on 10 May 2025. On 9 April 2026, Anthropic released the Advisor Strategy on the Claude Platform, implementing a functionally equivalent architecture. On 2 October 2025, Asawa et al. at UC Berkeley published a related approach. This paper presents a detailed chronological record, a structural comparison across all three works, and identifies the governance gap that remains unaddressed. The authors related patent filings for CRE (Claude Rule Enforcer, GB2604445.3) and HookBus (GB2608069.7) are presented as complementary governance solutions.
title AI-to-AI Feedback: Amplified Intelligence — Prior Art and Governance Implications for Multi-Model Advisory Architectures
topic AI-to-AI feedback
intelligence amplification
multi-model architecture
advisor strategy
prior art
AI governance
agentic systems
CRE
HookBus
url https://doi.org/10.5281/zenodo.19516174